Advances in plasma processing have facilitated growth in the semiconductor industry. During plasma processing, diagnostic tools may be employed to ensure high yield of devices being processed. Optical emission spectroscopy (OES) is often utilized as a diagnostic tool for gas-phase monitoring of etchants and etched products to maintain tight control of process parameters.
In the optical interrogation of plasma, there is a characteristic glow, i.e., specific optical emission spectrum, associated with a plasma discharge. Plasma discharge may have a spectral definition that may be a function of multiple variables including, but not limited to, constituent species, pressure, energy density, driving power, and the like. The spectrum, containing but not limited to deep ultra-violet (UV) through far infra-red (IR) wavelengths, may typically be observed employing a single channel spectrometer.
Optical interrogation of plasma may be performed by collecting the optical emission spectrum via a collimator through a quartz window of a plasma etch chamber. The spectral information, transmitted via a collector fiber optic bundle, may be measured by the signal channel of a spectrometer. With the spectral information from the optical interrogation, a considerable amount of information on constituent species may be collected and analyzed to provide guidance for process monitoring and control during plasma processing. However, optical interrogation of plasma employing OES has mainly been limited to qualitative analysis.
Variability, in particular, may be the main limitation hindering OES from being employed for quantitative analyses in the optical interrogation of plasma in a manufacturing environment. For example, variability may be observed from system-to-system in a device fabrication environment. System-to-system variability may manifest in differences in the conditions between each plasma processing system. In another example, system-to-system variability may be observed between measurement systems, i.e., spectrometer to spectrometer. In yet another example, system-to-system variability may be discerned in the differences in the setup of each distinct plasma processing system with each distinct spectrometer. As can be appreciated by those skilled in the art, variability from system-to-system in optical interrogation of plasma during processing in a manufacturing environment may provide a high level of uncertainty limiting OES from being employed as a quantitative tool for plasma monitoring and/or control.
Another source of variability that may limit OES from being employed for quantitative analyses in a manufacturing environment may be variation within a system. For example, the efficiency of coupling the fiber-optic bundle to the plasma chamber and/or to the spectrometer may be a source of variability within the system.
In another example, the geometry and mechanics of the plasma chamber may lead to variability, e.g., in-situ measurement of plasma signals, within the system. Plasma processing typically employs a low pressure relative to the atmosphere requiring a vacuum chamber. A window in the vacuum-chamber wall may need to be of a suitable material, e.g., the window may be constructed from quartz, to transmit in the desired wavelength dependent attenuation along the optical path to measure the plasma spectral signal. However, pressure control in some plasma processing system may employ a confinement ring setup which may partially occlude the optical path between the plasma and the spectrometer. Furthermore, the confinement rings may move relative to the interrogation window(s) depending on the desired plasma pressure and may also experience deposition and/or etching. Thus, the occlusion of the optical path, the deposition, and/or the etching may induce variability within the system making quantitative analysis employing OES impractical.
Variability due to degradation of components as a function of time, i.e., time-to-time variation, may be yet another source of variation impeding OES from being employed for quantitative analysis of plasma processes. For example, the aforementioned quartz window may be exposed to plasma during plasma processing and may experience deposition and/or etching. Thus over time, the quartz window may cloud up and may change the optical property of the window. Typically, clouding of the quartz window may result in lower plasma signal intensity in a nonlinear manner. In another time-to-time variability example, a fiber optic bundle may degrade in optical transmission efficiency as a function of time which may also result in lower plasma signal intensity in a nonlinear manner. As may be appreciated from the foregoing, time-to-time variability may provide yet another source of uncertainty limiting the OES from being employed as a quantitative tool.
In general, many of the variables that define plasma may be difficult to accurately measure in-situ. Also, there may be significant fluctuations at multiple time scales in plasma which may result in changes in spectral emission. Due to the variability associated with current optical interrogation of plasma employing OES, the task of quantitatively determining what plasma variables may cause emission changes may be extremely difficult. Thus, the use of OES may be limited to only qualitative applications such as end-point detection, leak identification, species identification, and the like.
A potential solution may entail employing controls to standardize OES to reduce variability at each step in the process. For example, calibrations may be performed to reduce variation between systems and/or instrument. Quartz windows may periodically be cleaned to reduce clouding. Fiber-optic bundles may be replaced to attain original transmission efficiency. Keyed connectors may be employed to mount optical couplers the same way to reduce set-up variability.
However, calibrations and controls may be amenable to laboratory environment but may not be conducive to a manufacturing environment. In high volume manufacturing facilities which may fabricate devices with over a hundred manufacturing steps at high throughput, calibrations and controls after each step may be impractical. The calibrations of uncontrolled variations and time related degradations may require specialized resources. Specialized resources may add cost to a manufacturing process that are extremely cost competitive. Careful calibrations and controls may add time overhead to processing time increasing the cost per device being manufactured and decreasing throughput. Thus, the controls may reduce variability without addressing the capability for quantitative OES measurements while penalizing the process with higher cost and lower throughput.
In view of the foregoing, there are desired methods and apparatus for employing OES as a quantitative tool for process monitoring and control during plasma processing.